The AI Trust Bucket
Introduction to AI Enablement
AI in Education and Quality of Work
The Role of AI in Problem Solving
Human Involvement in AI Processes
Navigating AI Recommendations in Consulting
The Balance of AI and Human Expertise
Evolving Use of AI in Professional Settings
Navigating the Non-Deterministic Nature of LLMs
Building Trust in AI: The User Experience
Understanding AI Integration Challenges
Establishing AI Strategy in Organizations
Avoiding the AI Hype: Practical Considerations
Fostering Adoption: Meeting Users Where They Are
Critical Thinking in the Age of AI
Episode 22: The AI Trust Bucket
If someone produces better work with AI, how do you know they're getting better at their job? Justin and Kellan talk about trust, accountability, and what it takes to help people use AI well. Along the way: a confident recommendation that needed another question, a camp agent named George, and knowing when ordinary process improvement is enough.
The Drip:
- The OpenAI research discussed this week: quality output, reasoning, and the question of whether people are building expertise.
- The Anthropic coding study and what people could explain after completing the task.
Inside The Bottle:
- A full trust bucket still needs boundaries.
- Why a promising demo needs to survive a typical month's work.
- Getting the leadership team aligned before choosing another tool.
- Meeting people where they are: three useful jobs for a camp agent.
- Keeping learning and accountability in the work, including the questions a manager will ask.
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